Evaluation of clustering techniques to predict surface roughness during turning of stainless-steel using vibration signals

Engineering

• Stainless Steel 100%
• Feature Extraction 100%
• Clustering Algorithm 66%
• Piezoelectric 33%
• Time Domain 33%
• Frequency Domain 33%
• Dimensionality 33%
• Process Parameter 33%
• Selection Method 33%
• Monitoring System 33%
• Process Monitoring 33%
• Machined Surface 33%
• Cutting Speed 33%
• Cutting Force 33%
• Cutting Condition 33%
• Extracted Feature 33%
• Metal Cutting 33%
• Spectral Signature 33%

Keyphrases

• Noise Clustering 50%
• Process Monitoring System 50%
• Filter Feature Selection Method 50%
• Cutting Feed 50%
• Steel Turning 50%